EM.starting.point: Randomly assigns a starting point for the EM algorithm
In CNVtools: A package to test genetic association with CNV data

Description Usage Arguments Value Author(s) References

This function should be invisible to most users, and is part of our the fitting routine using the EM algorithm. Our maximum likelihood procedure uses an iterative algorithm called Expectation-Maximization. This requires a starting point, chosen at random. EM.starting point randomly assigns this starting point.

1	EM.starting.point(d, trait = "binary")

`d`	The dataframe that needs to be initialized
`trait`	Can be either “binary” or ”eQTL”

Returns the input data frame with reasonable random starting values.

Vincent Plagnol vincent.plagnol@cimr.cam.ac.uk and Chris Barnes christopher.barnes@imperial.ac.uk

A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J. Royal Stat. Soc., vol. 39, pp. 1–38, 1977.

CNVtools documentation built on April 28, 2020, 6:06 p.m.